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GRATIS: GeneRAting TIme Series with diverse and controllable characteristics

Home Page: https://github.com/ykang/gratis

License: GNU General Public License v3.0

R 100.00%

statistical-computing mixture-autoregressive time-series data-generation

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Failure to simulate `seas_pacf` feature....

Hello, I had en error, when I tried to simulate seas_pacf feature:

x <- generate_ts_with_target(n = 2, ts.length = 60, freq = 1, seasonal = 0,
                             features = c('pacf_features'),
                             selected.features = c('seas_pacf'),
                             target = c(.01))

The output is:

Error in { : task 1 failed - "Unknown column `seas_pacf`
Backtrace:

What was done wrong?

Features from GUI appears to be very different from the features in CLI

For example:
https://ebsmonash.shinyapps.io/tsgeneration/
or at run_tsgeneration_app().

Where I can find any documentation of "all available features", and to which group they belong?

can it generate multivariate time series wit mixture continues and categorical data ?

great code thanks

only can it generate multivariate time series wit mixture continues and categorical data
meaning
several time series with continues data
and
several time series with categorical data

but there is some dependency between these time series ?

Error in unserialize(socklist[[n]]) : error reading from connection

Hi, I face another problem is when i set parameter 'parallel=TRUE', it usually shows error
'Error in unserialize(socklist[[n]]) : error reading from connection'
but 'parallel=FALSE'
Below is the console record.

features_groups$compengine_all
[1] "embed2_incircle_1" "embed2_incircle_2" "ac_9"
[4] "firstmin_ac" "trev_num" "motiftwo_entro3"
[7] "walker_propcross" "localsimple_mean1" "localsimple_lfitac"
[10] "sampen_first" "std1st_der" "spreadrandomlocal_meantaul_50"
[13] "spreadrandomlocal_meantaul_ac2" "histogram_mode_10" "outlierinclude_mdrmd"
[16] "fluctanal_prop_r1"
ts_features_compengine_sample[features_groups$compengine_all]
A tibble: 1 x 16
embed2_incircle… embed2_incircle… ac_9 firstmin_ac trev_num motiftwo_entro3 walker_propcross localsimple_mea…

1 0.397 0.698 0.357 5 0.0916 1.48 0.176 2
… with 8 more variables: localsimple_lfitac , sampen_first , std1st_der ,
spreadrandomlocal_meantaul_50 , spreadrandomlocal_meantaul_ac2 , histogram_mode_10 ,
outlierinclude_mdrmd , fluctanal_prop_r1

x <- generate_ts_with_target(n = 10, ts.length = 120, freq = 1, seasonal = 0,
                              features = c('compengine'), selected.features = c(features_groups$compengine_all),
                              target=c(ts_features_compengine_sample[features_groups$compengine_all]),  
parallel=TRUE)

 x <- generate_ts_with_target(n = 1, ts.length = 120, freq = 1, seasonal = 0,
                             features = c('compengine'), selected.features = c(features_groups$compengine_all),
                              target=c(ts_features_compengine_sample[features_groups$compengine_all]),  parallel=TRUE)

x <- generate_ts_with_target(n = 1, ts.length = 120, freq = 1, seasonal = 0,
+                              features = c('compengine'), selected.features = c(features_groups$compengine_all),
+                              target=c(ts_features_compengine_sample[features_groups$compengine_all]),  parallel=FALSE)

installation on mac

What R verison is needed?
I've tried to install for R 3.4.2., but got an error that tscomp in not suitable for R 3.4.2.

how to change the features?

I found this generator interesting, and tried to generate time series data.
However, when I tried to add one feature from the sample, I am stacked. How can I add features?

Following is the code to try to add 'seasonal.strength', but I found an error saying
"task 1 failed - "object 'seasonal.strength' of mode 'function' was not found"
How can I do?

Plus, how can I do for other features which are on the paper (Kang, Hyndman, Li 2018) ?

x <- generate_ts_with_target(n = 2,
ts.length = 360,
freq = 1,
seasonal = 0,
features = c('entropy', 'stl_features','seasonal.strength'),
selected.features = c('entropy', 'trend','seasonal.strength'),
target = c(0.2 0.9, 0.5)
)

Where I can find description for the features?

Where I can find description (hopefully, including some relevant equations) for the features?

For example time_var_shift.

I found some descriptions in tsfeatures package, but it doesn't cover all features, as well as the original paper.

gaps in index

I'm not sure why but the following code some how creates a gap at year 0004 July 2nd:

library(tsibble)
library(gratis)

set.seed(2022)
sim1 <- arima_model(frequency = 7,
                    p = 1, # non-seasonal AR order
                    d = 0, # non-seasonal order of differencing
                    q = 0, # non-seasonal MA order
                    P = 1, # seasonal AR order
                    D = 0, # seasonal order of differencing
                    Q = 1, # seasonal MA order
                    constant = 0, # intercept
                    phi = c(0.8), # AR parameters
                    theta = c(), # MA parameters
                    Phi = c(-0.4), # seasonal AR parameters
                    Theta = c(0.8), # seasonal MA parameters
                    sigma = 0.5 # sd of noise
) %>% 
  generate(length = 2000, nseries = 1)

scan_gaps(sim1)
#> # A tsibble: 1 x 1 [1D]
#>   index     
#>   <date>    
#> 1 0004-07-02

^{Created on 2022-04-21 by the reprex package (v2.0.1)}

What is the difference between several features, which apparantely related to seasonality?

What is the difference between following features?

seasonal_strength
seasonal_strength1
seasonal_strength2
seas_acf1
seas_pacf1

And in particular if seasonal_strength = 1 is it possible, that seas_acf1=0?

I looked through tsgeneration paper, but I didn't find. Please let me know if I miss something.

how to modified generate_ts_with_target function to other time series feature?

Hi,
I found this package is interesting and helpful to my research. and i want to use same approach to other feature that not in tsfeatures package.
I also found tsfeatures package support Compengine feature set from Fulcher. I want to try other feature set(catch22) https://github.com/chlubba/catch22 also from Fulcher.
How should I modified function to match other features not in tsfeatures?

Thanks for helping

Running time

Does it makes sense that running with

seasonal_strength = 0.9 -> takes ~5 hours
seasonal_strength = 0.9 -> takes more than 24 hours ??

I use laptop with 4 cores (8 threads), i7 cpu.

Doesn't work with Linux (Ubuntu)

Doesn't work with Linux (Ubuntu):

has the following error:

mcfork(): unable to create pipe
Calls: generator... <Anonymous> -> makeForkCluster -> newForkNode -> mcFork

Execution halted.

Clash with `generate` function in `fable` for ARIMA models

fable contains the function generate.ARIMA() so whenever fable is loaded it prefers to use fable::generate.ARIMA() for gratis::arima_model() instead of gratis::generate.Arima() causing the error like below. Perhaps the order of the classes should be swapped for arima_model() to c("forecast_ARIMA", "Arima", "ARIMA") so this won't be an issue?

library(gratis)
#> Registered S3 method overwritten by 'quantmod':
#>   method            from
#>   as.zoo.data.frame zoo
generate(arima_model())
#> # A tsibble: 1,000 x 3 [1]
#> # Key:       key [10]
#>    index key       value
#>    <dbl> <chr>     <dbl>
#>  1     1 Series 1 21.3  
#>  2     2 Series 1 -1.97 
#>  3     3 Series 1 20.3  
#>  4     4 Series 1 -2.52 
#>  5     5 Series 1 16.6  
#>  6     6 Series 1 -2.26 
#>  7     7 Series 1 14.6  
#>  8     8 Series 1 -0.454
#>  9     9 Series 1  9.97 
#> 10    10 Series 1 -0.756
#> # … with 990 more rows

library(fable)
#> Loading required package: fabletools
generate(arima_model())
#> Error in key_data(new_data): argument "new_data" is missing, with no default

class(arima_model())
#> [1] "forecast_ARIMA" "ARIMA"          "Arima"

^{Created on 2022-04-21 by the reprex package (v2.0.1)}

Session info

sessioninfo::session_info()
#> ─ Session info  👵🏿  👩‍👧‍👧  🇹🇹   ─────────────────────────────────────────────────
#>  hash: old woman: dark skin tone, family: woman, girl, girl, flag: Trinidad & Tobago
#> 
#>  setting  value
#>  version  R version 4.1.2 (2021-11-01)
#>  os       macOS Big Sur 10.16
#>  system   x86_64, darwin17.0
#>  ui       X11
#>  language (EN)
#>  collate  en_AU.UTF-8
#>  ctype    en_AU.UTF-8
#>  tz       Australia/Melbourne
#>  date     2022-04-21
#>  pandoc   2.17.1.1 @ /Applications/RStudio.app/Contents/MacOS/quarto/bin/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  package        * version    date (UTC) lib source
#>  anytime          0.3.9      2020-08-27 [1] CRAN (R 4.1.0)
#>  assertthat       0.2.1      2019-03-21 [1] CRAN (R 4.1.0)
#>  backports        1.3.0      2021-10-27 [1] CRAN (R 4.1.0)
#>  cli              3.2.0      2022-02-14 [1] CRAN (R 4.1.2)
#>  codetools        0.2-18     2020-11-04 [1] CRAN (R 4.1.2)
#>  colorspace       2.0-3      2022-02-19 [1] R-Forge (R 4.1.2)
#>  crayon           1.5.1      2022-03-26 [1] CRAN (R 4.1.2)
#>  curl             4.3.2      2021-06-23 [1] CRAN (R 4.1.0)
#>  DBI              1.1.1      2021-01-15 [1] CRAN (R 4.1.0)
#>  digest           0.6.29     2021-12-01 [1] CRAN (R 4.1.0)
#>  distributional   0.3.0      2022-01-05 [1] CRAN (R 4.1.2)
#>  doRNG            1.8.2      2020-01-27 [1] CRAN (R 4.1.0)
#>  dplyr            1.0.8.9000 2022-03-17 [1] Github (tidyverse/dplyr@8abb54b)
#>  ellipsis         0.3.2      2021-04-29 [1] CRAN (R 4.1.0)
#>  evaluate         0.14       2019-05-28 [1] CRAN (R 4.1.0)
#>  fable          * 0.3.1      2021-05-16 [1] CRAN (R 4.1.0)
#>  fabletools     * 0.3.2      2021-11-29 [1] CRAN (R 4.1.0)
#>  fansi            1.0.3      2022-03-24 [1] CRAN (R 4.1.2)
#>  farver           2.1.0      2021-02-28 [1] CRAN (R 4.1.0)
#>  fastmap          1.1.0      2021-01-25 [1] CRAN (R 4.1.0)
#>  foreach          1.5.2      2022-02-02 [1] CRAN (R 4.1.2)
#>  forecast         8.16       2022-01-10 [1] CRAN (R 4.1.2)
#>  fracdiff         1.5-1      2020-01-24 [1] CRAN (R 4.1.0)
#>  fs               1.5.2      2021-12-08 [1] CRAN (R 4.1.0)
#>  GA               3.2.2      2021-10-15 [1] CRAN (R 4.1.0)
#>  generics         0.1.2      2022-01-31 [1] CRAN (R 4.1.2)
#>  ggplot2          3.3.5      2021-06-25 [1] CRAN (R 4.1.0)
#>  glue             1.6.2      2022-02-24 [1] CRAN (R 4.1.2)
#>  gratis         * 1.0.0      2022-04-21 [1] Github (ykang/gratis@be360c2)
#>  gtable           0.3.0      2019-03-25 [1] CRAN (R 4.1.0)
#>  highr            0.9        2021-04-16 [1] CRAN (R 4.1.0)
#>  htmltools        0.5.2      2021-08-25 [1] CRAN (R 4.1.0)
#>  httpuv           1.6.5      2022-01-05 [1] CRAN (R 4.1.2)
#>  iterators        1.0.14     2022-02-05 [1] CRAN (R 4.1.2)
#>  knitr            1.37       2021-12-16 [1] CRAN (R 4.1.0)
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#>  pkgconfig        2.0.3      2019-09-22 [1] CRAN (R 4.1.0)
#>  polynom          1.4-1      2022-04-11 [1] CRAN (R 4.1.2)
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#>  quadprog         1.5-8      2019-11-20 [1] CRAN (R 4.1.0)
#>  quantmod         0.4.18     2020-12-09 [1] CRAN (R 4.1.0)
#>  R.cache          0.15.0     2021-04-30 [1] CRAN (R 4.1.0)
#>  R.methodsS3      1.8.1      2020-08-26 [1] CRAN (R 4.1.0)
#>  R.oo             1.24.0     2020-08-26 [1] CRAN (R 4.1.0)
#>  R.utils          2.11.0     2021-09-26 [1] CRAN (R 4.1.0)
#>  R6               2.5.1      2021-08-19 [1] CRAN (R 4.1.0)
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#>  reprex           2.0.1      2021-08-05 [1] CRAN (R 4.1.0)
#>  rlang            1.0.2.9000 2022-03-17 [1] Github (r-lib/rlang@22fe9e9)
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#>  tseries          0.10-50    2022-03-28 [1] CRAN (R 4.1.2)
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#>  TTR              0.24.3     2021-12-12 [1] CRAN (R 4.1.0)
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#> ──────────────────────────────────────────────────────────────────────────────

Does generate_ts_with_target function support all features in tsfeatures package?

i want to use the feature more than 26 features in your paper. Does this function support all features belowed?

Shiny app cannot generate data with error 'could not find function "ga_ts"'

I am attempting to use the shiny app launched by calling app_gratis(), however, there are a number of functions called in the shiny app that are no longer exported.

I was able to get the app working by manually exporting or recreating the missing functions.

install.packages("doParallel")
eval(parse(text=paste0('ga_ts', '<-gratis:::', 'ga_ts')))
eval(parse(text=paste0('fitness_ts', '<-gratis:::', 'fitness_ts')))
nsdiffs1 <- function(x) {
  c(nsdiffs = ifelse(frequency(x) == 1L, -1, forecast::nsdiffs(x)))
}

I am not sure if that's the best approach, but it looks sufficient to do some exploratory work.

Error in {: task 2 failed - "object 'x_acf1' of mode 'function' was not found"

Sorry, if I am misunderstanding this package. My end goal is to make many simulations of many time series. To test this I used tsfeatures on just one series. In the code below I am passing the results from tsfeatures to tsgeneration::generate_ts_with_target. The problem is I am getting the following error

#> Error in {: task 2 failed - "object 'x_acf1' of mode 'function' was not found"

tsgeneration::generate_ts_with_target(n = 1, ts.length = 60, freq = 7, seasonal = 1,
                        features = c('x_acf1', 'x_acf10','diff1_acf1','diff1_acf10',
                                     'diff2_acf1','diff2_acf10','seas_acf1','entropy',
                                     'lumpiness','flat_spots','crossing_points',
                                     'nperiods','seasonal_period','trend','spike','linearity',
                                     'curvature','e_acf1','e_acf10','seasonal_strength',
                                     'peak','trough','max_kl_shift','time_kl_shift',
                                     'mean','var','max_level_shift','time_level_shift',
                                     'max_var_shift','time_var_shift'),
                        selected.features = c('x_acf1', 'x_acf10','diff1_acf1','diff1_acf10',
                                              'diff2_acf1','diff2_acf10','seas_acf1','entropy',
                                              'lumpiness','flat_spots','crossing_points',
                                              'nperiods','seasonal_period','trend','spike','linearity',
                                              'curvature','e_acf1','e_acf10','seasonal_strength',
                                              'peak','trough','max_kl_shift','time_kl_shift',
                                              'mean','var','max_level_shift','time_level_shift',
                                              'max_var_shift','time_var_shift'),
                        target = c(0.336, 0.985,-0.1257,0.428,-0.486,0.458,0.403,
                                   0.913,1.0324,3,20,1,7,0.237,5.14e-04,0.772,
                                   1.47,-0.0761,0.068,0.631,1,3,0.208,42,3802,400176,0.464,
                                   38,0.519,37))
#> Error in {: task 2 failed - "object 'x_acf1' of mode 'function' was not found"

Created on 2018-10-05 by the reprex package (v0.2.0).

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